Can we use Reinforcement Learning to parse heterogeneity?
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Parsing heterogeneity and Identifying biotypes
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Multimodal Imaging Data fusion
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Multimodal Data fusion Steps
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Delay-Discount Factor
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DLPFC Multimodal Brain Pattern (n=1103)
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Explore the neural mechanisms of reinforcement learning in this 39-minute seminar by Dr. Poornima Kumar from McLean Hospital/Harvard Medical School. Delve into the functional and structural connectome underlying reinforcement learning processes. Examine computational models and their applications in understanding neural substrates of prediction error. Investigate the anatomy and circuitry of reinforcement learning, with a focus on its role in depression. Learn about reinforcement learning-based decision-making and its neural correlates. Discover methods for identifying structural and functional connectomes associated with reinforcement learning. Analyze the potential of reinforcement learning in parsing heterogeneity in major depressive disorder. Gain insights into multimodal imaging data fusion techniques and their application in identifying brain patterns related to reinforcement learning.
Functional and Structural Connectome of Reinforcement Learning